AIMC Topic: Support Vector Machine

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Two-Dimensional Light Scattering Anisotropy Cytometry for Label-Free Classification of Ovarian Cancer Cells via Machine Learning.

Cytometry. Part A : the journal of the International Society for Analytical Cytology Jul 16, 2019
We develop a single-mode fiber-based cytometer for the obtaining of two-dimensional (2D) light scattering patterns from static single cells. Anisotropy of the 2D light scattering patterns of single cells from ovarian cancer and normal cell lines is i...
Machine Learning Female Humans Support Vector Machine Ovarian Neoplasms Flow Cytometry Scattering, Radiation Microfluidic Analytical Techniques Anisotropy
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A comparison of three data mining time series models in prediction of monthly brucellosis surveillance data.

Zoonoses and public health Jul 15, 2019
The early and accurately detection of brucellosis incidence change is of great importance for implementing brucellosis prevention strategic health planning. The present study investigated and compared the performance of the three data mining techniqu...
Iran Data Mining Zoonoses Support Vector Machine Models, Statistical Population Surveillance Animals Brucellosis Humans
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Correlation-based channel selection and regularized feature optimization for MI-based BCI.

Neural networks : the official journal of the International Neural Network Society Jul 15, 2019
Multi-channel EEG data are usually necessary for spatial pattern identification in motor imagery (MI)-based brain computer interfaces (BCIs). To some extent, signals from some channels containing redundant information and noise may degrade BCI perfor...
Electroencephalography Brain-Computer Interfaces Humans Support Vector Machine
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A Real-Time Fire Detection Method from Video with Multifeature Fusion.

Computational intelligence and neuroscience Jul 14, 2019
The threat to people's lives and property posed by fires has become increasingly serious. To address the problem of a high false alarm rate in traditional fire detection, an innovative detection method based on multifeature fusion of flame is propose...
Fires Computing Methodologies Computer Systems Support Vector Machine Humans Color Algorithms
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A fast machine learning approach to facilitate the detection of interictal epileptiform discharges in the scalp electroencephalogram.

Journal of neuroscience methods Jul 13, 2019
BACKGROUND: Finding interictal epileptiform discharges (IEDs) in the EEG is a part of diagnosing epilepsy. Automated software for annotating EEGs of patients with suspected epilepsy can therefore help with reaching a diagnosis. A large amount of data...
Support Vector Machine Humans Signal Processing, Computer-Assisted Electroencephalography Cerebral Cortex Machine Learning Epilepsy Adult
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Image Processing-Based Detection of Pipe Corrosion Using Texture Analysis and Metaheuristic-Optimized Machine Learning Approach.

Computational intelligence and neuroscience Jul 11, 2019
To maintain the serviceability of buildings, the owners need to be informed about the current condition of the water supply and waste disposal systems. Therefore, timely and accurate detection of corrosion on pipe surface is a crucial task. The conve...
Corrosion Humans Support Vector Machine Machine Learning Water Supply Algorithms Image Processing, Computer-Assisted
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A Feasible Feature Extraction Method for Atrial Fibrillation Detection From BCG.

IEEE journal of biomedical and health informatics Jul 10, 2019
Atrial fibrillation (AF) is the most frequently occurring form of arrhythmia, which induces multiple fatal diseases and impairs the quality of life in patients; thus, the study of the diagnostic methods for detecting AF is clinically important. Here,...
Signal Processing, Computer-Assisted Atrial Fibrillation Ballistocardiography Middle Aged Support Vector Machine Machine Learning Algorithms Humans Female Aged Aged, 80 and over Male
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Melanoma Detection by Means of Multiple Instance Learning.

Interdisciplinary sciences, computational life sciences Jul 10, 2019
We present an application to melanoma detection of a multiple instance learning (MIL) approach, whose objective, in the binary case, is to discriminate between positive and negative sets of items. In the MIL terminology these sets are called bags and...
Databases, Factual Melanoma Support Vector Machine Humans Artificial Intelligence Algorithms
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Enhanced convolutional neural network for plankton identification and enumeration.

PloS one Jul 10, 2019
Despite the rapid increase in the number and applications of plankton imaging systems in marine science, processing large numbers of images remains a major challenge due to large variations in image content and quality in different marine environment...
Animals Zooplankton Support Vector Machine Deep Learning Pacific Ocean Video Recording Ecological Parameter Monitoring Datasets as Topic
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Machine Learning Models can Detect Aneurysm Rupture and Identify Clinical Features Associated with Rupture.

World neurosurgery Jul 9, 2019
BACKGROUND: Machine learning (ML) has been increasingly used in medicine and neurosurgery. We sought to determine whether ML models can distinguish ruptured from unruptured aneurysms and identify features associated with rupture.
Adult Sensitivity and Specificity Male Female Aged Hypertension Diabetes Mellitus Support Vector Machine Middle Aged Comorbidity Case-Control Studies Humans Machine Learning Retrospective Studies Aneurysm, Ruptured Intracranial Aneurysm Hyperlipidemias Smoking
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